3 papers
cs.LG2025
No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers
Jiajun He, Yuanqi Du, Francisco Vargas +5
We consider the sampling problem, where the aim is to draw samples from a distribution whose density is known only up to a normalization constant. Recent breakthroughs in generativ…
cs.LG2025
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
Jihao Andreas Lin, Shreyas Padhy, Bruno Mlodozeniec +2
Scaling hyperparameter optimisation to very large datasets remains an open problem in the Gaussian process community. This paper focuses on iterative methods, which use linear syst…
cs.LG2024
A Generative Model of Symmetry Transformations
James Urquhart Allingham, Bruno Kacper Mlodozeniec, Shreyas Padhy +5
Correctly capturing the symmetry transformations of data can lead to efficient models with strong generalization capabilities, though methods incorporating symmetries often require…